1. Field of the Invention
The present invention relates to an image processing technique for raising the image quality of a digital image by applying a correction.
2. Description of the Related Art
Techniques for analyzing a digital image obtained by a digital camera or scanner, etc., and applying a correction so as to obtain an excellent image quality have been proposed. For example, many pixels in an image are distributed over dark gradations in case of underexposure, and many pixels in an image are distributed over bright gradations in case of overexposure. In a correction of inappropriate brightness thus ascribable to underexposure or overexposure, there is a technique that involves analyzing a histogram of pixels in the image and correcting brightness so as to obtain an appropriate histogram.
A technique proposed in recent years involves determining a feature in a digital image, detecting a digital image of a specific object (e.g., a person's face) and applying a specialized correction to the object.
Japanese Patent Application Laid-Open No. 2007-18073 discloses an image processing technique that includes: determining density correction coefficients obtained by analyzing an overall digital image that has been input and density correction coefficients obtained by analyzing the area of a person's face; comparing both coefficients to evaluate the degree of compatibility thereof and revising the density correction coefficients of the local area in accordance with the degree of compatibility; and executing correction processing upon blending the revised density correction coefficients of the local area and the density correction coefficients of the overall digital image at a prescribed blending ratio.
The conventional correction of a digital image is such that both overall-image correction parameters for optimizing the overall image and local-image correction parameters for optimizing a local face area are used in the same correction processing, namely a density (or brightness) correction. The parameters used when correction processing is executed also have the same parameter format, namely that of a one-dimensional look-up table (1D-LUT), with respect to the γ coefficient and brightness. As a result, the blending of overall-image correction parameters and local-image correction parameters can be performed by simple addition (superposition).
However, correction processing has become more complex and multifarious with the aim of achieving a further improvement in the image quality of digital images, and besides the conventional correction of brightness only, correction of color cast due to loss of color balance has become important.
In addition to techniques for dealing with so-called “failed” images, such as images with exposure errors or poor white balance, techniques for correcting flesh color or the color of the sky or greenery to obtain a more desirable color and techniques for correcting an image so as to appear sharper are also important.
It is necessary to select, depending upon the nature of correction processing, an algorithm that is the most efficacious and involves little computational load. However, the formats of the optimum parameters for this purpose differ depending on the nature of the correction processing and algorithm.
For example, although a one-dimensional look-up table (1D-LUT) for dealing with brightness is the most effective method in order to correct brightness, correcting the overall image using a 3×3 rotation matrix is the most effective method for correcting color cast. Furthermore, often an across-the-board constant is used in order to improve the saturation (chroma) of the overall image. If a plurality of correction processes are executed, parameters having a format conforming to each correction process become necessary, but parameters having different formats can be simply added.
By using correction parameters relating to one correction process at a time, it is possible to blend, at a prescribed ratio, an image corrected by a correction value for optimizing an overall digital image and an image corrected by a correction value for optimizing a face area.
However, in order to execute a plurality of correction processes with such method, a large-capacity memory for holding the original image and the image after correction is required. This means that an increase in cost is unavoidable.